Corneal biomechanical properties are important for the diagnosis of corneal diseases, individualized design and prognosis of corneal surgery. Clinical available devices such as Ocular Response Analyzer (ORA) and Corneal Visualization Scheimpflug Technology (Corvis ST) can provide corneal biomechanics related parameters, while corneal elastic modulus cannot be extracted directly from them at present. The aim of this study is to suggest a method to determine corneal elastic modulus based on the results of Corvis ST test according to Reissner’s theory on the relation between stress and small displacement in shallow spherical shell. Five rabbits (10 eyes) and 10 healthy humans (20 eyes) were measured with Corvis ST to obtain the normal range of corneal elastic modulus. Results showed Corneal elastic modulus of rabbit was 0.16 MPa to 0.35 MPa, human corneal elastic modulus was 0.16–0.30 MPa. Rabbit corneas were also measured at different intraocular pressures (IOP), and results showed corneal elastic modulus, first applanation time (A1T) and stiffness parameter (SP-A1) were positively correlated with IOP. Deformation amplitude (DA), the second applanations time (A2T), and peak distance (PD) were negatively correlated with IOP. Finite element method was used to simulate the Corvis measurements according to the calculated elastic modulus and the simulated corneal apical displacements were agreement with experimental results in general. The method to determine corneal elastic modulus based on Corvis test according to the relationship between force and displacements of shallow spherical shell is convenient and effective.

Human CLCN7 encodes voltage-gated chloride channel 7 (ClC-7); mutations of CLCN7 lead to osteopetrosis which is characterized by increased bone mass and impaired osteoclast function. In our previous clinical practice, we noticed that osteopetrosis patients with CLCN7 mutations had some special deformities in craniofacial morphology and tooth dysplasia. It is unclear whether these phenotypes are the typical features of CLCN7 involved osteopetrosis and whether ClC-7 could regulate the development of craniofacial bone and tooth in some signaling pathways.

Background: To compare the dynamic corneal response (DCR) and tomographic parameters of thin normal cornea (TNC) with thinnest corneal thickness (TCT) (≤ 500 µm), forme fruste keratoconus (FFKC) and mild keratoconus (MKC) had their central corneal thickness (CCT) matched by Scheimpflug imaging (Pentacam) and corneal visualization Scheimpflug technology (Corvis ST). Methods: CCT were matched in 50 eyes with FFKC, 50 eyes with MKC, and 53 TNC eyes with TCT ≤ 500 µm. The differences in DCR and tomographic parameters among the three groups were compared. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic significance of these parameters. Back propagation (BP) neural network was used to establish the keratoconus diagnosis model. Results: Fifty CCT-matched FFKC eyes, 50 MKC eyes and 50 TNC eyes were included. The age and biomechanically corrected intraocular pressure (bIOP) did not differ significantly among the three groups (all P > 0.05). The index of height asymmetry (IHA) and height decentration (IHD) differed significantly among the three groups (all P < 0.05). IHD also had sufficient strength (area under the ROC curves (AUC) > 0.80) to differentiate FFKC and MKC from TNC eyes. Partial DCR parameters showed significant differences between the MKC and TNC groups, and the deflection amplitude of the first applanation (A1DA) showed a good potential to differentiate (AUC > 0.70) FFKC and MKC from TNC eyes. Diagnosis model by BP neural network showed an accurate diagnostic efficiency of about 91%. Conclusions: The majority of the tomographic and DCR parameters differed among the three groups. The IHD and partial DCR parameters assessed by Corvis ST distinguished FFKC and MKC from TNC when controlled for CCT.

Purpose: The aim of this study was to provide a method to determine corneal nonlinear viscoelastic properties based on the output data of corneal visualization Scheimpflug technology (Corvis ST).Methods: The Corvis ST data from 18 eyes of 12 healthy humans were collected. Based on the air-puff pressure and the corneal displacement from the Corvis ST test of normal human eyes, the work done by the air-puff attaining the whole corneal displacement was obtained. By applying a visco-hyperelastic strain energy density function of the cornea, in which the first-order Prony relaxation function and the first-order Ogden strain energy were employed, the corneal strain energy during the Corvis ST test was calculated. Then the work done by the air-puff attaining the whole corneal displacement was completely regarded as the strain energy of the cornea. The identification of the nonlinear viscoelastic parameters was carried out by optimizing the sum of difference squares of the work and the strain energy using the genetic algorithm.Results: The visco-hyperelastic model gave a good fit to the data of corneal strain energy with time during the Corvis ST test (R² > 0.95). The determined Ogden model parameter μ ranged from 0.42 to 0.74 MPa, and α ranged from 32.76 to 55.63. The parameters A and τ in the first-order Prony function were 0.09–0.36 and 1.21–1.95 ms, respectively.Conclusion: It is feasible to determine the corneal nonlinear viscoelastic properties based on the corneal contour information and air-puff pressure of the Corvis ST test.

Purpose: This study aims to evaluate the validity of corneal elastic modulus (E) calculated from corneal visualization Scheimpflug technology (Corvis ST) in diagnosing keratoconus (KC) and forme fruste keratoconus (FFKC).Methods: Fifty KC patients (50 eyes), 36 FFKC patients (36 eyes, the eyes were without morphological abnormality, while the contralateral eye was diagnosed as clinical keratoconus), and 50 healthy patients (50 eyes) were enrolled and underwent Corvis measurements. We calculated E according to the relation between airpuff force and corneal apical displacement. One-way analysis of variance (ANOVA) and receiver operating characteristic (ROC) curve analysis were used to identify the predictive accuracy of the E and other dynamic corneal response (DCR) parameters. Besides, we used backpropagation (BP) neural network to establish the keratoconus diagnosis model.Results: 1) There was significant difference between KC and healthy subjects in the following DCR parameters: the first/second applanation time (A1T/A2T), velocity at first/second applanation (A1V/A2V), the highest concavity time (HCT), peak distance (PD), deformation amplitude (DA), Ambrosio relational thickness to the horizontal profile (ARTh). 2) A1T and E were smaller in FFKC and KC compared with healthy subjects. 3) ROC analysis showed that E (AUC = 0.746) was more accurate than other DCR parameters in detecting FFKC (AUC of these DCR parameters was not more than 0.719). 4) Keratoconus diagnosis model by BP neural network showed a more accurate diagnostic efficiency of 92.5%. The ROC analysis showed that the predicted value (AUC = 0.877) of BP neural network model was more sensitive in the detection FFKC than the Corvis built-in parameters CBI (AUC = 0.610, p = 0.041) and TBI (AUC = 0.659, p = 0.034).Conclusion: Corneal elastic modulus was found to have improved predictability in detecting FFKC patients from healthy subjects and may be used as an additional parameter for the diagnosis of keratoconus.

Background: Aqueous humor flows regularly from posterior chamber to anterior chamber, and this flow much involves intraocular pressure, the eye tissue nutrition and metabolism. Purpose: To visualize and measure the intraocular flow regular pattern of aqueous humor. Method: Intraocular flow in the vitro eyeball is driven to simulate the physiological aqueous humor flow, and the flow field is measured by Particle Image Velocimetry(PIV). Fluorescent particle solution of a certain concentration was infused into the root of Posterior Chamber(PC) of vitro rabbit eye to simulate the generation of aqueous and was drained out at a certain hydrostatic pressure from the angle of Anterior Chamber(AC) to represent the drainage of aqueous. PIV method was used to record and calculate the flow on the midsagittal plane of the eyeball. Results: Velocity vector distribution in AC has been obtained, and the distribution shows symmetry feature to some extent. Fluorescent particle solution first fills the PC as it is continuously infused, then surges into AC through the pupil, flows upwards toward the central cornea, reflecting and scattering, and eventually converges along the inner cornea surface towards the outflow points at the periphery of the eyeball. Velocity values around the pupillary margin are within the range of 0.008-0.012 m/s, which are close to theoretical values of 0.0133 m/s, under the driving rate of 100 μl/min. Conclusions: Flow field of aqueous humor can be measured by PIV method, which makes it possible to study the aqueous humor dynamics by experimental method. Our study provides a basis for experimental research on aqueous humor flow; further, it possibly helps to diagnose and treat eye diseases as shear force damage of ocular tissues and destructions on corneal endothelial cells from the point of intraocular flow field.